| Summary: | Abstract With the rapid development of information technology and network technology and the rapid popularization of computers and intelligent devices, network video media have gradually replaced traditional media and became the main carrier of information production, storage, dissemination, sharing, and use. However, digital information can be easily copied, modified, and disseminated, which leads to the problem of network video copyright theft which is very prominent. Aiming at the copyright problem of sports video, this paper proposes an idea of using LOGO to identify the copyright of sports video, which can automatically and effectively detect whether the video is genuine or not. Firstly, encrypted LOGO is added to the video by encryption technology, and then, LOGO recognition technology is used to distinguish whether the LOGO is missing in the video, so as to distinguish the legitimacy of the video. In addition, aiming at the shortcomings of traditional LOGO recognition technology, this paper proposes a LOGO detection and recognition technology based on convolution neural network. This method improves the traditional histogram algorithm, proposes an analysis algorithm based on non-uniform block HSV histogram, and introduces region weighting coefficients to extract key frames from the video. Then, the convolution neural network is used to extract the features of the key frames of the video. Finally, the features of the sample LOGO are matched to complete the LOGO detection and recognition. Simulation results show that the effect of feature extraction using convolution neural network is better. Compared with the traditional LOGO recognition technology, the LOGO detection and recognition technology based on convolution neural network proposed in this paper has better detection and recognition performance. It effectively detects the LOGO information in the video and realizes the recognition of whether the video is genuine or not.
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